• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.373-380
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• 2007

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over and overlapping as well as demand splitting are considered. Also, maximum number of setups for each time period is not limited. For this LSSP, we have formulated a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we have developed an efficient heuristic algorithm by combining decomposition scheme with local search procedure. Test results show that the developed heuristic algorithm finds good quality (in practice, even better) feasible solutions using far less computation time compared with the CPLEX, a competitive MIP solver.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.113-125
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• 2008

This paper presents a model for designing cellular manufacturing systems (CMS) by integrating system cost, machine reliability, and preventive maintenance (PM) planning. In a CMS, a part is processed using alternative process routes, each consisting of a sequence of visits to machines. Thus, a level of 'system reliability' is associated with the machines along the process route assigned to a part type. Assuming machine reliabilities to follow the Weibull distribution, the model assigns the machines to cells, and selects, for each part type, a process route which maximizes the overall system reliability and minimizes the total costs of manufacturing operations, machine underutilization, and inter-cell material handling. The model also incorporates a reliability based PM plan and an algorithm to implement the plan. The algorithm determines effective PM intervals for the CMS machines based on a group maintenance policy and thus minimizes the maintenance costs subject to acceptable machine reliability thresholds. The model is a large mixed integer linear program, and is solved using LINGO. The results point out that integrating PM in the CMS design improves the overall system reliability markedly, and reduces the total costs significantly.

• Journal of the military operations research society of Korea
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• v.34 no.3
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• pp.1-12
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• 2008

Design of supply chain network (SCN) is required to optimize every factor in SCN and to provide a long-term and strategic decision-making. A mathematical model can not reflect the real world because design of SCN contains variables and stochastic factors according to status of its system. This paper presents the designing methodology of military SCN using the mathematical model and the simulation model. It constructs SCN to minimize its total costs using the Mixed Integer Programming (MIP) model. And we solve problems of a vehicle assignment and routing through adaptation of experiment parameters repeatedly in the simulation model based on the results from the MIP model. We implement each model with CPLEX and AutoMod, and experiment to reconstruct SCN when the Logistic Support Unit is restricted to support military units. The results from these experiments show that the proposed method can be used for a design of military SCN.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.304-308
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• 1998

With the advances in concurrent engineering, schedulability has become an important design issue in machine loading and routing procedure. In this paper, four rules to improve schedulability of loading and routing are formulated as a mixed-integer programming model based on machine, routing and tool flexibilities. In this model, these rules are represented as an objective function or constraints. The impact of rules on the quality of schedules for the result of loading and routing is measured with makespan, throughput and average machine utilization.

• Journal of the military operations research society of Korea
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• v.5 no.2
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• pp.3-14
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• 1979

본 논문은 체계적인 연산법(Algorithm)을 연구, 개발하여 여산산출에 중요한 역할을 하는 mixed integer programming 문제를 계산하기 위하여 첫째로, 많은 투자수단 또는 계획중 가장 합리적인 (이익율이 높은) 수단을 정하는 Weingartner의 여산산출모델 (Capital Budgeting Model)을 간단히 검토해 보고, 둘째로 위의 검토에서 얻어진 개념에 따른 이 모델의 문제점들을 모색해 보며 마지막으로 기획분야의 어떤 기간동안 자원확보(확대)를 가능케 하는 여산산출 문제를 해결할 수 있는 방안이나 체계적 연산법을 개발해 보고자 한다. 이러한 휴계적 연산법은 (함축적인 또는 부분적인) 열권방식 (Enumeration Technique)을 이용함으로써 위에 제시된 문제를 해결하는데 용역 할 것이다.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.131-145
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• 1993

This paper deals with scheduling problem of the chemical process system where aircraft parts go through a given sequence of tanks filled with chemical solutions. The system has two hoists which move carriers holding the parts between tanks. A mixed integer programming model is developed from which a maximum throughput schedule can be found for the hoist movements. To show the validity of the model, a real world problem is solved and the results are compared with those with an existing approach.

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.75-102
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• 1992

지난 수십년간 수많은 신호교차로제어모형이 제시되어 왔으나 과포화교차로를 특별히 다루는 기법은 거의 없었다. 본고에서는 과포화상태의 신호교차로제어를 위한 최적화모형이 제시된다. 지체도최소화나 연동폭최대화가 전통적인 제어목표로 사용되어 왔으나 혼잡교차로 제어에는 생산성최대화(maximum productivity)가 적절하며 본 모형에 사용되었다. 제시된 최적화모형은 Mixed Integer Linear Programming의 형태를 취한다. 본 모형은 두 개의 교차로 문제에 적용되었으며, 모형화 과정에 사용된 가정들의 적절함이 민감도분석에 의해 증명되었다. 최적해의 검증을 위하여 microscopic simulation model인 TRAF-NETSIM을 사용하였다.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.589-605
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• 1996

Recycling of used products and components has been considered as one of promising strategies for resolving environmental problems. In this respect, most manufacturing companies begin to consider possible recycling (e.q., reuse or re-production) of the components contained in their products. The primary objective of this research is to develop a multiple criteria decision making model for systematic management of recycle-oriented manufacturing components. The production planning problem of recycle-oriented manufacturing components is first formulated as a multiobjective mixed 0-1 integer programming model with three conflicting objectives. An interactive multiple criteria decision making method is then developed for solving the mathematical model. Also, an Input/Output analysis software is developed to help practitioners apply the model to real problems without much knowledge on computers and mathematical programming. A numerical example is used in examining the validity of the proposed model and to investigate the impact of the input variables on recycling production strategy.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.369-382
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• 2014

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.37-48
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• 2014

Fighter squadron flight scheduling is the integrated air operation plan that is an important role for improving pilot's flight skill and maintaining combat readiness by efficient using available all air resources including pilot, aircrafts, air-weapons, fuel and supporting facilities etc. Korea airforce, however, has a limit as to an effective flight operation due to manual flight scheduling with scheduler's own experience and intuition. Therefore, in our study, we propose the optimization model of flight scheduling based on mixed integer programming. This model includes several constraints of realistic and essential quantified data related with flight schedule and can assign appropriate pilots optimally which are distinctive three type's solutions : flight, alert and duty crew schedules. Proposed solution method can be improved pilot's capability and allocated further air resources systematically and efficiently. In addition, it can be reduced a workload of flight scheduler and minimized obstructed factors of flight safety. Finally, we demonstrate the experiment's results for the check of efficiency and validity of this model.